The present invention relates to data driven editing of rib centerlines extracted from medical image data, and more particularly, to interactive data driven correction of inaccurate portions of rib centerlines to achieve better accuracy of rib centerline extraction and rib unfolding.
Locating rib metastases and fractures in chest CT scans typically involves reading hundreds of axial CT slices to visually track changes in rib cross-section area. Manual reading of CT scans is rather time consuming and rib anomalies are frequently missed in practice due to human error. Automatic extraction of rib anatomical centerlines can be used to enhance the visualization of an unfolded rib cage. Accordingly, accurate detection of rib centerlines is an important task that aids radiologists in finding metastases and fractures in an efficient manner. However, inaccurate detection can jeopardize the accuracy of a diagnosis, for example by causing the radiologist to miss a rib lesion. Since the automatic rib centerline extraction task cannot consistently provide 100% accuracy, an interactive correction system that allows a radiologist to correct rib centerlines when the automatic extraction does not provide satisfactory results is desirable.